Object detection systems and methods, such as pedestrian detection systems and methods, can be implemented in automatic driver assistance systems to provide lane detection, obstacle detection, traffic sign recognition, pedestrian detection, and/or other types of detection. Such object detection systems and methods often implement support vector machine (SVM) classifiers to assist with classifying analyzed images into an object class or non-object class. Today's SVM-based object detection systems and methods tend to be computationally intensive, requiring significant data bandwidth that present challenges for real-time implementation. Accordingly, although existing SVM-based object detection systems and associated methods have been generally adequate for their intended purposes, they have not been entirely satisfactory in all respects.